Turning Raw Data Into Smart Data

Your organization may have a big data platform in place, but do you have a smart data strategy?

Big Data Analytics Masters Degrees: 20 Top Programs

(click image for larger view and for slideshow)

Autodesk, the design and engineering software firm perhaps best known for its venerable AutoCAD program, has some data management advice for enterprises: Think beyond big data and focus on "smart data."

What's that? Well, it depends. In Autodesk's core business of providing 3D technologies and visualization tools, smart data might mean embedding additional details in virtual 3D models -- essential design information such as structural and material characteristics for multiple components of a building or bridge.

And according to Autodesk senior vice president Amar Hanspal, enterprises can apply the same smart data strategy to give their business data broader meaning. This smart data approach can make it easier for people to work collaboratively and can help 'democratize' analytical tools that bring data science skills to the masses. "Smart data has enough information and context so that the person looking at it can make a decision," said Hanspal in a phone interview with InformationWeek.

You might think "smart data" sounds like yet another vacuous buzzword in an industry already inundated with them. And you might have a point. But the concept does have merit, particularly as enterprises struggle to find value in their growing stockpiles of digital information.

Here's how Hanspal defined the term: "It's simply data that people can make decisions on." Alternatively, organizations can use smart data to drive automated processes.
In an automation scenario, for instance, smart data might involve wireless sensors and other data sources in a building. Combined, these devices would feed information to automated controls that manage basic building functions, such as turning the lights on or off.

Obviously, this is a simple example. But in the world of computer-aided design, builders are taking the smart data concept to a much higher level. "I visited a hospital site before Christmas, and the people who were doing the design were modeling every joint they're putting into the hospital," said Hanspal. "For instance, the airflow system is a big deal because of infections." That means designers on the project are creating detailed models that make sure air flows efficiently and safely through door openings and throughout the building.

"People have been increasing the amount of information they're putting into these building designs so later on they can make decisions with greater levels of confidence," Hanspal added.

Preventive maintenance is another area that can benefit from smart data. For instance, if you design a machine for certain stress loads, sensor and simulation data can predict in real time when repairs are needed. "Simulation is our word for analytics. We typically call engineering analytics 'simulation,'" said Hanspal. "We can link these two things together: real-time information and a simulation of conditions to predict what corrective action needs to be taken."

Hanspal added that smart data can help "democratize" data science as well. "We've always believed in the concept of democratization, and in getting tools in the hands of as many people as we can," Hanspal said. "Some analytical tools can be made accessible to many people."

Energy analysis tools, for instance, can enable architects to position a building for maximum daylight. "That's a simple example, but that's a lot of information," said Hanspal. "You talk about big data. We're crunching through weather stations -- all these places where we get the data. We're making the decision for the architect really simple because we're bringing it down to two or three [choices] on the position of the building, the slope of the roof, and building finishes."

"That kind of analytical tool you can democratize," Hanspal added.

It's innovate or die in the IT equipment industry, and that goes double in the server business. Get our State Of Servers: Full, Fast And Diverse report for key findings from our recent survey. (Free registration required.)

Most IT teams have their conventional databases covered in terms of security and business continuity. But as we enter the era of big data, Hadoop, and NoSQL, protection schemes need to evolve. In fact, big data could drive the next big security strategy shift.

Why should big data be more difficult to secure? In a word, variety. But the business won’t wait to use it to predict customer behavior, find correlations across disparate data sources, predict fraud or financial risk, and more.